Learn how to efficiently extract and analyze web content using Tinq.ai's Article Extractor, both through API and a simple web interface. This guide also shows how to integrate the tool with other Tinq.ai features for a powerful content workflow.

Sometimes, writing essays may not be the most straightforward thing to do. Especially when the topic is assigned. For this reason, having guidance on where to get started is primordial when writing an essay. In order to do that, AI tools have become prevalent in the writing great essays. In

By using Tinq.ai to write more engaging tweets, you can connect with your audience and build a strong social media presence.

In this tutorial, you will learn how to create a simple Discord app and a Bot that reads incoming chats from a server using Python.

Automate brand sentiment analysis on tweets using Tinq.ai, Zapier, and Airtable.

Text classification (or categorization) is one of the most common natural language processing (NLP) tasks. It consists in associating an unstructured text with a tag, which corresponds to a specific class.

In this tutorial, we will learn how to build a simple, yet powerful feedback form using Tinq.ai and Airtable. We will use Tinq-ai's sentiment analysis tool to analyze the user's feedback, and classify them as "neutral", "positive" or "negative".

Check a document for plagiarism and then use the rewriter to rewrite that content as unique content, free of plagiarism. That means that this content passes plagiarism checkers such as Turnitin.

Perform sentiment analysis on customer feedback with no code using Tinq AI, Typeform, and Airtable.

Tinq AI is a production-ready NLP toolkit wrapped into a REST API. It allows you to perform various NLP tasks such as summarization, paraphrasing, named-entity recognition, sentiment analysis, and much more. All that without the hassle of training models. If you don't feel like reading, you can watch this video